BACKGROUND: The bowtie-filter in cone-beam CT (CBCT) causes spatially nonuniform x-ray beam often leading to eclipse artifacts in the reconstructed image. The artifacts are further confounded by the patient scatter, which is therefore patient-depende...
BACKGROUND: Recent developments in artificial intelligence (AI) systems have enabled advancements in endoscopy. Deep learning systems, using convolutional neural networks, have allowed for real-time AI-aided detection of polyps with higher sensitivit...
Many therapies in clinical trials are based on single drug-single target relationships. To further extend this concept to multi-target approaches using multi-targeted drugs, we developed a machine learning pipeline to unravel the target landscape of ...
In the present study, a bioelectrochemical reactor (BEC) was utilized to treat two types of real saline produced water (PW). BEC was designed based on the combination of electrocoagulation (EC) process with halophilic microorganisms, and it was asses...
OBJECTIVES: The differential between high-grade glioma (HGG) and metastasis remains challenging in common radiological practice. We compare different natural language processing (NLP)-based deep learning models to assist radiologists based on data co...
BACKGROUND: In recent years, deep learning methods have been successfully used for chest x-ray diagnosis. However, such deep learning models often contain millions of trainable parameters and have high computation demands. As a result, providing the ...
Neural networks : the official journal of the International Neural Network Society
Sep 4, 2023
Deep Neural Networks (DNNs) have become an important tool for modeling brain and behavior. One key area of interest has been to apply these networks to model human similarity judgements. Several previous works have used the embeddings from the penult...
Neural networks : the official journal of the International Neural Network Society
Sep 4, 2023
Designing efficient and accurate network architectures to support various workloads, from servers to edge devices, is a fundamental problem as the use of Convolutional Neural Networks (ConvNets) becomes increasingly widespread. One simple yet effecti...
Neural networks : the official journal of the International Neural Network Society
Sep 3, 2023
Graph Neural Networks (GNNs) have been successfully applied to graph-level tasks in various fields such as biology, social networks, computer vision, and natural language processing. For the graph-level representations learning of GNNs, graph pooling...
Human pose estimation is the basis of many downstream tasks, such as motor intervention, behavior understanding, and human-computer interaction. The existing human pose estimation methods rely too much on the similarity of keypoints at the image feat...
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